Content-Aware Subspace Low-Rank Tensor Recovery for Hyperspectral Image Restoration-Reference-Cited by-同舟云学术

Content-Aware Subspace Low-Rank Tensor Recovery for Hyperspectral Image Restoration

Published:2023 Issue: Volume:61 Page:1-19
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Xiao Xueyao¹^ORCID,Zhang Wei²^ORCID,Chang Yi¹^ORCID,Cao Shuning¹,He Wei³^ORCID,Fang Houzhang⁴^ORCID,Yan Luxin¹^ORCID

Affiliation:

1. National Key Laboratory of Science and Technology on Multispectral Information Processing, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China

2. Artificial Intelligence Center, Peng Cheng Laboratory, Shenzhen, China

3. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

4. School of Computer Science and Technology, Xidian University, Xi'an, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10238728.pdf?arnumber=10238728

Reference93 articles.

1. Total-Variation-Regularized Low-Rank Matrix Factorization for Hyperspectral Image Restoration

2. Hyperspectral Image Restoration via Subspace-Based Nonlocal Low-Rank Tensor Approximation

3. Low-Rank Matrix Factorization under General Mixture Noise Distributions

4. Subspace Clustering for Hyperspectral Images via Dictionary Learning with Adaptive Regularization

5. Remote Sensing Image Stripe Noise Removal: From Image Decomposition Perspective